Sunday, November 27, 2011

Jmol

Jmol is an open-source Java viewer for three-dimensional chemical structures. It is cross-platform, running on Windows, Mac OS X, and Linux/Unix systems. 


Features:
- Multi-language
- Supports all major web browsers: Internet Explorer, Mozilla and Firefox, Safari, Google Chrome, Opera, etc.
- High-performance 3D rendering with no hardware requirements
- Animations
- Surfaces
- Vibrations


- Reactions


- Orbitals


- Support for unit cell and symmetry operations
- Schematic shapes for secondary structures in biomolecules
- Measurements (distance, angle, torsion angle)




You can get the latest version of Jmol here :)

Source: SourceForge

JChemPaint

JChemPaint is a Java program for drawing 2D chemical structures. It is open source and free software. Since it is written on Java, it runs on any computing platform and operating system for which a Java Virtual Machine has been implemented (like Linux, Windows, etc). If your system does not have Java Virtual Machine, you can get it here


Features:
Drawing and deletion of single, double, triple and stereo bonds
Colouring of atom types, and other rendering settings
Editing of atomic charges, isotopes and hydrogen count.
Loading and saving of structures in Chemical Markup Language (CML) and as MDL MOL files and SDF files (loading only).
Automated Structure Layout, also known as Structure Diagram Generation.
Loading structures from the Internet using CAS or NSC number.
- Normalization of structures, currently limited to aromaticity detection.
Saving bitmap pictures of the structures.
Saving structures as graphics (PNG, BMP, Scalable Vector Graphics (SVG)).
Postscript printing
- Translated into several languages: Dutch, French, German, Polish, Portuguese and Spanish.

You can get it here :)

Source: SourceForge

Thursday, November 24, 2011

ChemPup

ChemPup is a unique software system built from Puppy Linux with numerous useful chemistry programs


Features


Office Productivity:
OpenOffice.org-3.0 - full office productivity suite compatible with MS Office
JabRef - reference manager that syncs with OOO3
Firefox - web browser


Chemistry Programs:
GElemental - periodic table packed with information on each element



Nomen - simple nomenclature tool
JChemPaint - 2D chemical structure editor


JMol - 3D chemical structure viewer and force-field minimizer


Avogadro - 3D chemical structure builder with built in force-fields and molecular dynamics simulations


OpenBabel - chemical file-type converter
SciFinder Scholar - online scientific journal database (must have site.prf file added from school administrator)
ChemTool and GNotebook - spreadsheet templates with useful chemical equations, conversions, etc.

You can get ChemPup here (requires registration)


ChemPup is built from Puppy Linux 4.2.1 which is a very smallflexibleportable and complete operating system. How is it so different and useful?


1. ChemPup loads its entire system into RAM memory.
Although this process takes slightly longer to boot (depending on hardware configurations) it ultimately runs very fast on even low-spec (old) computers.

2. You don't ever have to install ChemPup on any computer.
No installation required. Simply boot from the ChemPup CD or USB flashdrive.

3. You may install ChemPup to a hard-drive partition (advanced).
This can be done in two ways, "full" or "frugal" installation options. A "frugal" install is recommended as it may be installed on a NTFS formatted hard-drive along side MS Windows. This does require some additional working knowledge and the user is STRONGLY ENCOURAGED to consult the www.puppylinux.org documentation before considering this option. The only significant advantage is that the CD or DVD is no longer needed at boot-up if ChemPup has been installed


Source: ChemToolBox

Wednesday, November 23, 2011

Linux Live USB Creator

One of the advantages of using Ubuntu is that we can "try" it without installing it on our PC. This system is usually called Live system, LiveCD (via CD), or LiveUSB (using USB). Imagine that we can use it on every PC (which is compatible, for sure). And what's even cooler is that we can access files on that PC. Cool, right?

To try Ubuntu via CD or flashdisc, we have to own Linux CD or we have to make our flashdisc to be Linux-bootable. How? On this post, I want to share about a program which can help you make your flashdisc to be Linux-bootable. The name of the program is LiLi, or Linux Live USB Creator. Check the tutorial below...


What are the things that you have to prepare?

1. Flashdisc for sure, with 1GB of minimum capacity. Move all of the data from the flashdisc, because it will be formatted later
2. LiLi USB program, you can download it here. Then install it on your Windows PC
3. ISO distro Linux file. Ubuntu, for example. You can download it here. Choose the server location whiches closer with your location, to make the download process faster.



The steps for creating Ubuntu-bootable flashdisc

Open the LiLi program, this is how it looks like...


STEP 1: CHOOSE YOUR KEY
Choose your flashdisc drive


STEP 2: CHOOSE A SOURCE
Choose the ISO/IMG/ZIP icon. Then select the ISO file that you have downloaded. LiLi will correct that ISO file and show a success message if there is no mistake


ISO/IMG/ZIP


ISO Ubuntu file or another Linux


Checking first, then ready

STEP 3: PRESISTENCE
For now, just skip this step, or let it on its default settings. What is presistence? Presistence will create virtual saving media on your flashdisc. The function is for saving file when using LiveUSB. Of course this presistence also needs more space in flashdisc

STEP 4: OPTIONS
Give checklist on "Hide created files on key" and "Format the key in FAT32". Uncheck the last option "Enable Launching LinuxLive in Windows"


Give checklist on the first and second options only

Before step 5:
Recheck all the settings, if needed, from the first

STEP 5: CREATE
Click the lightning icon to begin process. LiLi will give warning if there's something wrong, don't worry



WAIT UNTIL FINISH
After finished, there will be "Your LinuxLive key is now up and ready" notice


After you have done installing, you have to restart your PC or laptop and change the main booting into USB drive or CD room. If you do not change it, it will be back again to Windows. To enter the booting menu, press the F2, F5, or F9, depends on your PC or laptop. The process will take time around 10-15 minutes. Then, it is up to you whether you only want to try or install it. 


Source: Goji's blog, Ka Febri's blog
Translator: Wanda Septa Luthfiasari (myself)

Tuesday, November 22, 2011

Methods Used in Computational Chemistry

A single molecular formula can represent a number of molecular isomers. Each isomer is a local minimum on the energy surface created from the total energy as a function of the coordinates of all the nuclei. A stationary point is a geometry such that the derivative of the energy with respect to all displacements of the nuclei is zero. A local (energy) minimum is a stationary point where all such displacements lead to an increase in energy. The local minimum that is lowest is called the global minimum and corresponds to the most stable isomer. If there is one particular coordinate change that leads to a decrease in the total energy in both directions, the stationary point is a transition structure and the coordinate is the reaction coordinate. This process of determining stationary points is called geometry optimization.

The determination of molecular structure by geometry optimization became routine only after efficient methods for calculating the first derivatives of the energy with respect to all atomic coordinates became available. Evaluation of the related second derivatives allows the prediction of vibrational frequencies if harmonic motion is estimated. More importantly, it allows for the characterization of stationary points. The frequencies are related to the eigenvalues of the Hessian matrix, which contains second derivatives. If the eigenvalues are all positive, then the frequencies are all real and the stationary point is a local minimum. If one eigenvalue is negative (i.e., an imaginary frequency), then the stationary point is a transition structure. If more than one eigenvalue is negative, then the stationary point is a more complex one, and is usually of little interest. When one of these is found, it is necessary to move the search away from it if the experimenter is looking solely for local minima and transition structures.

The total energy is determined by approximate solutions of the time-dependent Schrödinger equation, usually with no relativistic terms included, and by making use of the Born–Oppenheimer approximation, which allows for the separation of electronic and nuclear motions, thereby simplifying the Schrödinger equation. This leads to the evaluation of the total energy as a sum of the electronic energy at fixed nuclei positions and the repulsion energy of the nuclei. A notable exception are certain approaches called direct quantum chemistry, which treat electrons and nuclei on a common footing. Density functional methods and semi-empirical methods are variants on the major theme. For very large systems, the relative total energies can be compared using molecular mechanics. The ways of determining the total energy to predict molecular structures are:

1. Ab Initio methods

The programs used in computational chemistry are based on many different quantum-chemical methods that solve the molecular Schrödinger equation associated with the molecular Hamiltonian. Methods that do not include any empirical or semi-empirical parameters in their equations – being derived directly from theoretical principles, with no inclusion of experimental data – are called ab initio methods. This does not imply that the solution is an exact one; they are all approximate quantum mechanical calculations. It means that a particular approximation is rigorously defined on first principles (quantum theory) and then solved within an error margin that is qualitatively known beforehand. If numerical iterative methods have to be employed, the aim is to iterate until full machine accuracy is obtained

The simplest type of ab initio electronic structure calculation is the Hartree–Fock scheme, an extension of molecular orbital theory, in which the correlated electron–electron repulsion is not specifically taken into account; only its average effect is included in the calculation. As the basis set size is increased, the energy and wave function tend towards a limit called the Hartree–Fock limit. Many types of calculations (known as post-Hartree–Fock methods) begin with a Hartree–Fock calculation and subsequently correct for electron–electron repulsion, referred to also as electronic correlation. As these methods are pushed to the limit, they approach the exact solution of the non-relativistic Schrödinger equation. In order to obtain exact agreement with experiment, it is necessary to include relativistic and spin orbit terms, both of which are only really important for heavy atoms. In all of these approaches, in addition to the choice of method, it is necessary to choose a basis set. This is a set of functions, usually centered on the different atoms in the molecule, which are used to expand the molecular orbitals with the LCAO ansatz. Ab initio methods need to define a level of theory (the method) and a basis set.

The Hartree–Fock wave function is a single configuration or determinant. In some cases, particularly for bond breaking processes, this is quite inadequate, and several configurations need to be used. Here, the coefficients of the configurations and the coefficients of the basis functions are optimized together.

The total molecular energy can be evaluated as a function of the molecular geometry; in other words, the potential energy surface. Such a surface can be used for reaction dynamics. The stationary points of the surface lead to predictions of different isomers and the transition structures for conversion between isomers, but these can be determined without a full knowledge of the complete surface



2. Density functional methods

Density functional theory methods are often considered to be ab initio methods for determining the molecular electronic structure, even though many of the most common functionals use parameters derived from empirical data, or from more complex calculations. In DFT, the total energy is expressed in terms of the total one-electron density rather than the wave function. In this type of calculation, there is an approximate Hamiltonian and an approximate expression for the total electron density. DFT methods can be very accurate for little computational cost. Some methods combine the density functional exchange functional with the Hartree–Fock exchange term and are known as hybrid functional methods.

3. Semi-empirical and empirical methods

Semi-empirical quantum chemistry methods are based on the Hartree–Fock formalism, but make many approximations and obtain some parameters from empirical data. They are very important in computational chemistry for treating large molecules where the full Hartree–Fock method without the approximations is too expensive. The use of empirical parameters appears to allow some inclusion of correlation effects into the methods.

Semi-empirical methods follow what are often called empirical methods, where the two-electron part of the Hamiltonian is not explicitly included. For π-electron systems, this was the Hückel method proposed by Erich Hückel, and for all valence electron systems, the extended Hückel method proposed by Roald Hoffmann.

4. Molecular mechanics

In many cases, large molecular systems can be modeled successfully while avoiding quantum mechanical calculations entirely. Molecular mechanics simulations, for example, use a single classical expression for the energy of a compound, for instance the harmonic oscillator. All constants appearing in the equations must be obtained beforehand from experimental data or ab initio calculations.

The database of compounds used for parameterization is crucial to the success of molecular mechanics calculations. A force field parameterized against a specific class of molecules, for instance proteins, would be expected to only have any relevance when describing other molecules of the same class.

These methods can be applied to proteins and other large biological molecules, and allow studies of the approach and interaction (docking) of potential drug molecules

5. Methods for solids

Computational chemical methods can be applied to solid state physics problems. The electronic structure of a crystal is in general described by a band structure, which defines the energies of electron orbitals for each point in the Brillouin zone. Ab initio and semi-empirical calculations yield orbital energies; therefore, they can be applied to band structure calculations. Since it is time-consuming to calculate the energy for a molecule, it is even more time-consuming to calculate them for the entire list of points in the Brillouin zone.

Source: Wikipedia

Monday, November 21, 2011

Computational Chemistry Predicts Flu Mutations

Researchers in the US have shown how it might be possible to use computational chemistry to predict which mutations in a key influenza virus protein could lead to dangerous new strains of the disease.
Haemagglutinin is a protein which influenza viruses use to bind to specific sugar molecules on the surface of the host cell. It is thought that the more tightly the haemagglutinin binds, the more infective the virus could be. The avian influenza virus, for example, has a particular haemagglutinin that binds to sugar molecules found in cells in the upper respiratory tract of birds. These sugars are slightly different to those found in the cells of the human upper respiratory tract, but if bird flu haemagglutinin mutated in a way that favoured stronger binding to the 'human' sugar, it could result in a strain of the virus that could be more easily transmitted between humans. 
However, it is not known which mutations in the viral protein might cause this stronger binding. Now, Peter Kasson and colleagues at the University of Stanford in California have shown how molecular dynamics simulations might provide useful clues about which amino acids in the protein are important for binding.
Using data from x-ray crystallography of haemagglutinin bound to the bird-type sugar, the researchers carried out a series of molecular dynamics simulations to determine which amino acids in the protein had most influence on the binding event. They combined this information with data on the sequence of avian influenza haemagglutinin to pinpoint potential sites of mutation in the DNA that could result in the relevant amino acids being altered - and therefore have a possible impact on the binding.
Limited experimental data do exist which suggest that the predictive method could work, but Kasson concedes that more experimental work is needed to confirm that the method is accurate. 'Mutations that change the binding specificity from bird-type sugars to human-type sugars could be a high-risk mutation for human-to-human transmission,' Kasson says. 'If we can predict these mutations in advance it would give us much better data for surveillance and control.'
Peter Coombs, an expert on the influenza virus at the National Institute of Medical Research in the UK, says 'If computer simulations can predict mutations that might result in the virus binding more strongly to the host cell then we can create these mutations in the lab and test them.' This would provide better insights into the interaction of haemagglutinin and cell surface ligands. 'It is an interesting approach and if it comes to fruition it could be very useful. However, a lot more experimental work is needed to confirm that the method can provide useful predictions.'

Part of the haemagglutinin protein
Part of the haemagglutinin head with a small sugar molecule in orange. The mutation sites most strongly predicted to destabilise ligand binding by haemagglutinin are shown in yellow

Source: RSC

Sunday, November 20, 2011

History of Computational Chemistry


Building on the founding discoveries and theories in the history of quantum mechanics, the first theoretical calculations in chemistry were those of Walter Heitler and Fritz London in 1927. The books that were influential in the early development of computational quantum chemistry include Linus Pauling and E. Bright Wilson's 1935 Introduction to Quantum Mechanics – with Applications to Chemistry, Eyring, Walter and Kimball's 1944 Quantum Chemistry, Heitler's 1945 Elementary Wave Mechanics – with Applications to Quantum Chemistry, and later Coulson's 1952 textbook Valence, each of which served as primary references for chemists in the decades to follow.
With the development of efficient computer technology in the 1940s, the solutions of elaborate wave equations for complex atomic systems began to be a realizable objective. In the early 1950s, the first semi-empirical atomic orbital calculations were carried out. Theoretical chemists became extensive users of the early digital computers. A very detailed account of such use in the United Kingdom is given by Smith and Sutcliffe. The first ab initio Hartree–Fock calculations on diatomic molecules were carried out in 1956 at MIT, using a basis set of Slater orbitals. For diatomic molecules, a systematic study using a minimum basis set and the first calculation with a larger basis set were published by Ransil and Nesbet respectively in 1960. The first polyatomic calculations using Gaussian orbitals were carried out in the late 1950s. The first configuration interaction calculations were carried out in Cambridge on the EDSAC computer in the 1950s using Gaussian orbitals by Boys and coworkers. By 1971, when a bibliography of ab initio calculations was published, the largest molecules included were naphthalene and azulene. Abstracts of many earlier developments in ab initio theory have been published by Schaefer
In 1964, Hückel method calculations (using a simple linear combination of atomic orbitals (LCAO) method for the determination of electron energies of molecular orbitals of π electrons in conjugated hydrocarbon systems) of molecules ranging in complexity from butadiene and benzene to ovalene, were generated on computers at Berkeley and Oxford. These empirical methods were replaced in the 1960s by semi-empirical methods such as CNDO
In the early 1970s, efficient ab initio computer programs such as ATMOL, GAUSSIAN, IBMOL, and POLYAYTOM, began to be used to speed up ab initio calculations of molecular orbitals. Of these four programs, only GAUSSIAN, now massively expanded, is still in use, but many other programs are now in use. At the same time, the methods of molecular mechanics, such as MM2, were developed, primarily by Norman Allinger
One of the first mentions of the term "computational chemistry" can be found in the 1970 book Computers and Their Role in the Physical Sciences by Sidney Fernbach and Abraham Haskell Taub, where they state "It seems, therefore, that 'computational chemistry' can finally be more and more of a reality." During the 1970s, widely different methods began to be seen as part of a new emerging discipline of computational chemistry. The Journal of Computational Chemistry was first published in 1980.


Source: Wikipedia

Computational Chemistry


Computational chemistry is a branch of chemistry that uses principles of computer science to assist in solving chemical problems. It uses the results of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures and properties of molecules and solids. Its necessity arises from the well-known fact that apart from relatively recent results concerning the hydrogen molecular ion, the quantum n-body problem cannot be solved analytically, much less in closed form. While its results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials.
Examples of such properties are structure, absolute and relative (interaction) energies, electronic charge distributions, dipoles and higher multipole moments, vibrational frequencies, reactivity or other spectroscopic quantities, and cross sections for collision with other particles.
The methods employed cover both static and dynamic situations. In all cases the computer time and other resources (such as memory and disk space) increase rapidly with the size of the system being studied. That system can be a single molecule, a group of molecules, or a solid. Computational chemistry methods range from highly accurate to very approximate; highly accurate methods are typically feasible only for small systems. Ab initio methods are based entirely on theory from first principles. Other (typically less accurate) methods are called empirical or semi-empirical because they employ experimental results, often from acceptable models of atoms or related molecules, to approximate some elements of the underlying theory.
Both ab initio and semi-empirical approaches involve approximations. These range from simplified forms of the first-principles equations that are easier or faster to solve, to approximations limiting the size of the system (for example, periodic boundary conditions), to fundamental approximations to the underlying equations that are required to achieve any solution to them at all. For example, most ab initio calculations make the Born–Oppenheimer approximation, which greatly simplifies the underlying Schrödinger equation by freezing the nuclei in place during the calculation. In principle, ab initio methods eventually converge to the exact solution of the underlying equations as the number of approximations is reduced. In practice, however, it is impossible to eliminate all approximations, and residual error inevitably remains. The goal of computational chemistry is to minimize this residual error while keeping the calculations tractable.
In some cases, the details of electronic structure are less important than the long-time phase space behavior of molecules. This is the case in conformational studies of proteins and protein-ligand binding thermodynamics. Classical approximations to the potential energy surface are employed, as they are computationally less intensive than electronic calculations, to enable longer simulations of molecular dynamics. Furthermore, cheminformatics uses even more empirical (and computationally cheaper) methods like machine learning based on physicochemical properties. One typical problem in cheminformatics is to predict the binding affinity of drug molecules to a given target


Source: Wikipedia

Saturday, November 19, 2011

Opening

Good morning all :D so, I created another blog.. Well, I mean this one. This blog will contain everything about computational chem, for my final exam's score. Such as the explanation about computational chem itself, how to create USB Linux Chempup and how to get it, the use of Chempup, and how to use computational chem software in Chempup. I will update this blog until the next 4 weeks. Sooo, I hope whoever reading it will enjoy. And, thanks for coming to my blog and reading it :D

Cheers!